DP-900 Describe core data concepts Practice Test 8 — 15 Questions

Question 1

A social media application displays the number of posts each user has created. After a user submits a new post, the count must reflect the update across all servers within a few seconds. Which data consistency model best describes this requirement?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Eventual consistency. Eventual consistency is correct because the requirement allows a few seconds for the update to propagate across all servers, meaning the system does not guarantee immediate uniformity but will converge to the same count eventually. This is typical in distributed systems like social media applications where high availability and partition tolerance are prioritized over immediate consistency, often using techniques like asynchronous replication.

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Strong consistency

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Sequential consistency

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Causal consistency

Question 2

A logistics company collects data from fleet sensors. Each sensor sends a JSON message containing the vehicle ID, timestamp, and a variable set of measurements such as engine temperature, tire pressure, and fuel level. The structure of the JSON message differs between sensor types and sometimes includes optional fields. How should this data be classified?

Accepted Answer

Semi-structured data. The data is semi-structured because it conforms to a schema (JSON format with fields like vehicle ID and timestamp) but allows variability in structure, such as optional fields and different sets of measurements per sensor type. This flexibility is a hallmark of semi-structured data, which does not require a rigid tabular schema like structured data but still contains tags or markers to separate data elements.

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Structured data

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Unstructured data

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Relational data

Question 3

A logistics company collects sensor data from delivery trucks. Each sensor sends a JSON message that includes a fixed set of core fields (truck ID, timestamp) but also includes optional fields such as temperature, humidity, and engine diagnostics depending on the sensor type. The JSON structure varies between messages. How should this data be classified?

Accepted Answer

Semi-structured data. The JSON messages contain a fixed set of core fields (truck ID, timestamp) but also include optional fields that vary per message, meaning the data has a flexible schema. This mixture of structured fields and variable attributes is the defining characteristic of semi-structured data, which does not require a rigid schema like a relational table but still has organizational properties (e.g., key-value pairs). In Azure, this type of data is commonly stored in services like Azure Cosmos DB or Azure Blob Storage with JSON format.

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Structured data

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Unstructured data

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Relational data

Question 4

A company receives customer order data from its online store in a CSV file. Each line contains fields like OrderID, CustomerName, Product, Quantity, and OrderDate. This data is best described as:

Accepted Answer

Structured data. A is correct because the CSV file contains data that conforms to a strict tabular schema with predefined columns (OrderID, CustomerName, Product, Quantity, OrderDate) and consistent data types per column. This rigid, row-and-column format with a fixed schema is the defining characteristic of structured data, which can be directly loaded into a relational database or Azure SQL Database without transformation.

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Semi-structured data

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Unstructured data

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Transactional data

Question 5

A company stores product information such as product ID, name, price, and category in a relational database with rows and columns. This data is best described as:

Accepted Answer

Structured data. Structured data conforms to a predefined schema with rows and columns, making it easily searchable and queryable via SQL. The product information (ID, name, price, category) fits this model exactly, as each attribute has a fixed data type and is stored in a relational database table.

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Semi-structured data

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Unstructured data

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Transactional data

Question 6

A database system must ensure that when a transfer of funds between two accounts is processed, if the system crashes after debiting the first account but before crediting the second, the database automatically undoes the debit. This property is best described as:

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. If the system crashes after debiting one account but before crediting the other, the database's transaction log records the partial changes, and during recovery, the database engine (e.g., SQL Server's ARIES recovery model) performs an automatic rollback of the uncommitted transaction, undoing the debit to maintain atomicity.

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Consistency

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Isolation

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Durability

Question 7

A company stores employee records in a database. Each employee record contains an EmployeeID (unique), Name, Department, and HireDate. The EmployeeID is used to uniquely identify each employee. Which data concept does the EmployeeID represent?

Accepted Answer

Primary key. The EmployeeID is used to uniquely identify each employee record, which is the defining characteristic of a primary key. In relational databases, a primary key enforces entity integrity by ensuring each row has a unique, non-null identifier. This aligns with the core data concept of a primary key as the unique identifier for a table.

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Index

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Foreign key

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Unique constraint

Question 8

A healthcare application stores patient vital signs readings. Each reading is a JSON document with fields: PatientID, Timestamp, HeartRate, BloodPressure (systolic and diastolic). The application frequently queries for all readings of a specific patient within a time range, and the schema varies occasionally (e.g., new optional fields are added). How should this data be classified?

Accepted Answer

Semi-structured. The data is semi-structured because it is stored as JSON documents, which have a flexible schema that can vary between records (e.g., new optional fields can be added). JSON documents are self-describing and do not require a fixed schema like relational tables, but they still have organizational properties (fields like PatientID, Timestamp) that distinguish them from unstructured data like plain text or images. The application's queries on specific fields (PatientID, Timestamp) further confirm the data has structure, but the schema flexibility rules out structured or relational classifications.

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Structured

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Unstructured

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Relational

Question 9

A company has a database that processes millions of small credit card transactions per second for payment authorization. They also need to run complex reports that aggregate transaction data over months to detect fraud patterns. Which type of workload describes the payment authorization process?

Accepted Answer

OLTP (Online Transaction Processing). The payment authorization process involves high-volume, low-latency transactions that read, insert, and update individual records in real time. This is the classic definition of OLTP (Online Transaction Processing), which is optimized for ACID-compliant, row-based operations on current data. The scenario explicitly states 'millions of small credit card transactions per second,' which aligns with OLTP workloads like order entry or banking.

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OLAP (Online Analytical Processing)

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HTAP (Hybrid Transactional/Analytical Processing)

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ETL (Extract, Transform, Load)

Question 10

A retail company stores product inventory data in a fixed-schema table with columns for ProductID, ProductName, QuantityInStock, and ReorderLevel. How should this data be classified?

Accepted Answer

Structured data. This data is classified as structured data because it conforms to a fixed schema with clearly defined columns (ProductID, ProductName, QuantityInStock, ReorderLevel) and data types, stored in a relational table. Structured data is highly organized, easily queryable via SQL, and follows a rigid schema, which matches the description of the inventory table.

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Semi-structured data

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Unstructured data

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Streaming data

Question 11

A bank processes a fund transfer transaction. The system debits $100 from Account A and then credits $100 to Account B. If the system crashes after debiting Account A but before crediting Account B, the database automatically reverts the debit. Which ACID property ensures this behavior?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. If any part of the transaction fails (e.g., a crash after debiting Account A but before crediting Account B), the entire transaction is rolled back, reverting any partial changes like the debit. This all-or-nothing behavior is the core of atomicity in database systems.

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Consistency

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Isolation

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Durability

Question 12

A social media platform stores user posts as JSON documents. Each document contains text content, image URLs, timestamps, and user tags. The structure is consistent for most fields, but users can add custom key-value pairs. How should this data be classified?

Accepted Answer

Semi-structured data. The data is semi-structured because it has a consistent schema for most fields (text, image URLs, timestamps, user tags) but allows custom key-value pairs, which introduces schema flexibility. JSON documents inherently support this mix of fixed and variable attributes, fitting the semi-structured data classification. This aligns with Azure Cosmos DB's handling of JSON items, where each document can have a different set of properties.

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Structured data

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Unstructured data

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Relational data

Question 13

A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?

Accepted Answer

Semi-structured data. The customer feedback forms contain a mix of structured fields (CustomerID, SubmissionDate) that follow a fixed schema and unstructured fields (free-text Comments) plus optional fields (Rating, ProductCategory) that may or may not be present. This combination of schema-optional and schema-fixed data within the same record is the hallmark of semi-structured data, which does not require a rigid schema like a relational table but still has some organizational properties (e.g., tags or key-value pairs). In Azure, this data is well-suited for storage in Azure Cosmos DB (using JSON documents) or Azure Blob Storage with metadata, rather than a strictly relational database.

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Structured data

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Unstructured data

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Relational data

Question 14

A banking application processes a funds transfer transaction consisting of two steps: debit $100 from Account A and credit $100 to Account B. If the system crashes after debiting Account A but before crediting Account B, the database automatically reverts the debit, restoring Account A to its original balance. Which ACID property guarantees this behavior?

Accepted Answer

Atomicity. Atomicity ensures that a transaction is treated as a single, indivisible unit of work. In this scenario, the debit and credit are part of one transaction; if the system crashes after the debit but before the credit, the database management system (DBMS) automatically rolls back the entire transaction, undoing the debit to restore Account A's original balance. This all-or-nothing behavior is the defining characteristic of atomicity.

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Consistency

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Isolation

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Durability

Question 15

A company stores customer data in a SQL Server table with fixed columns (CustomerID, Name, Email, SignupDate). The company also stores application logs as JSON documents and marketing images as JPEG files. Which data type describes the customer data?

Accepted Answer

Structured data. Customer data stored in a SQL Server table with fixed columns (CustomerID, Name, Email, SignupDate) follows a rigid schema where each row has the same set of columns with defined data types. This conforms to the relational model, making it structured data. Structured data is organized into rows and columns with a fixed schema, enabling efficient querying via SQL.

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Semi-structured data

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Unstructured data

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Relational data